Episode 57 — 5.3 Reduce Exposure: PII, PHI, Data Sharing, Anonymization, Masking
Failed to add items
Add to cart failed.
Add to wishlist failed.
Remove from wishlist failed.
Follow podcast failed
Unfollow podcast failed
Episode 57 — 5.3 Reduce Exposure: PII, PHI, Data Sharing, Anonymization, Masking
-
Narrated by:
-
Written by:
About this listen
This episode focuses on exposure reduction strategies that DA0-002 tests when prompts involve sharing data, protecting privacy, or deciding what to include in reports and extracts. You will define PII as information that can identify a person directly or indirectly, and PHI as health-related information tied to an individual, then connect those definitions to handling constraints. Data sharing is treated as a controlled act that must align to purpose, audience, and policy, not an automatic byproduct of analysis. You will cover masking as a way to hide sensitive portions of values while preserving utility for tasks like testing or limited reporting. Anonymization is addressed as a higher bar that aims to prevent reidentification, and you will learn why true anonymization is difficult and depends on context and auxiliary data. The objective is to recognize exposure cues in scenarios and choose safeguards that preserve usefulness while reducing risk.